AI Udaan syllabus · Week 5–6
NumPy for Machine Learning & AI
NumPy provides fast numerical arrays that power scikit-learn, TensorFlow, and most Python ML code. AI Udaan teaches NumPy properties, vectorization, broadcasting, reshaping, and matrix operations before your first regression model.
Why NumPy after Pandas
Pandas handles tabular data; NumPy handles the numeric matrices models actually train on. Converting a feature column to a NumPy array is a daily step in ML pipelines.
Topics in AI Udaan
Week 5 covers box plots, NumPy introduction, vectorization, broadcasting, and reshaping. Week 6 adds real-world NumPy examples, scalar/vector/matrix multiplication, and the introduction to machine learning types and scikit-learn.
Covered in AI Udaan
- NumPy arrays and properties
- Vectorization and broadcasting
- Matrix multiplication basics
- Bridge to scikit-learn regression
Go deeper with the full bootcamp
This guide is a free overview. AI Udaan is a 16-week mentor-led Python with AI/ML bootcamp — live classes, assignments, projects, certificate, and career support for learners across Nepal.
FAQ
Is NumPy required for TensorFlow in AI Udaan?
Yes. NumPy literacy from Weeks 5–6 supports both scikit-learn models and later TensorFlow/Keras neural network modules.
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